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About the Role
Take direct technical ownership over key parts of our AI ecosystem, ensuring intelligence feels invisible, thoughtful, and deeply integrated into our financial workflows. Operate with true technical autonomy to build clean, high-impact architecture.
Responsibilities
- Spend the majority of your time writing production code, implementing robust backend software components, and building reliable asynchronous execution pipelines alongside AI models.
- Development of deterministic-agentic bridges, ensuring complex autonomous tasks operate within predictable, secure, and compliant financial boundaries.
- Take full responsibility for bringing machine learning models out of research prototypes and into stable, highly performant production code.
- Collaborate closely with backend and data engineers to take agentic workflows from prototype to reliable, monitored production systems — with practical experience across retrieval, memory, context, and orchestration layers.
- Model the engineering craft using modern AI tools (Cursor, Claude Code, Copilot) as a core part of your daily workflow to accelerate iteration, architecture design, and system delivery.
Requirements
- 7–15 years of overall software engineering experience, including 3+ years in senior AI engineering or ML engineering roles.
- Deep software engineering fundamentals and proven hands-on experience designing, writing, and scaling production-grade machine learning and AI systems.
- Strong programming skills in Python alongside asynchronous execution models.
- Experience with modern LLM tooling and orchestration frameworks such as LangGraph and Microsoft Agent Framework (MAF).
- Practical experience taking agentic systems into production, not just prototyping them.
- Understanding of agentic design patterns, including Plan-and-Solve / Plan-and-Execute, ReAct (Reason + Act), and Reflection / Reflexion, and ability to explain trade-offs.
- Hands-on experience with prompt engineering and context engineering.
- Practical experience building RAG pipelines and semantic search architectures, including chunking, embeddings, hybrid search, and re-ranking.
- Experience with vector databases such as PostgreSQL/pgvector or Milvus is valued.
- Knowledge of how to measure AI systems in production — quality, cost, and latency — using evaluation frameworks such as RAGAS and DeepEval.
- Experience handling personally identifiable information and sensitive data with LLMs in a regulated environment.
- Comfort designing and shipping AI systems within strict security, compliance, and audit boundaries.
- Ability to manage deadlines comfortably, balancing complete end-to-end task ownership with a clear commitment to sharing technical context.
- Fluent English speaking and writing skills.
Skills
- Python
- Asynchronous execution models
- LLM tooling
- Orchestration frameworks
- LangGraph
- Microsoft Agent Framework (MAF)
- Agentic systems
- Agentic design patterns
- Plan-and-Solve / Plan-and-Execute
- ReAct (Reason + Act)
- Reflection / Reflexion
- Prompt engineering
- Context engineering
- RAG pipelines
- Semantic search architectures
- Chunking
- Embeddings
- Hybrid search
- Re-ranking
- Vector databases
- PostgreSQL/pgvector
- Milvus
- AI evaluation
- RAGAS
- DeepEval
- PII handling
- Data privacy
- Regulated environments
- Security
- Compliance
- Audit boundaries
Location
- Lisbon
- Dubai
- Kyiv
- Lviv
- Remote
Work Type
- Full-time
- Remote
Experience Level
- Senior
- 7-15 years overall software engineering
- 3+ years AI/ML engineering
Benefits
- 24 days of annual leave
- Dedicated paid sick leave
- Observance of Public Holidays
- Two consecutive 4-day work weeks annually (after first year)
- Top-of-the-line hardware
- Home office stipend
- Dedicated learning budget
- Clear, accelerated path toward executive-level leadership
About the Company
- UMO is a stealth-mode FinTech venture aiming to evolve the way people experience money by building a unified, AI-powered, yet deeply human modern money platform across fiat, crypto, and investments - subject to regulatory approvals.
- The platform is being designed to break down traditional barriers to money across access, assets, and experience, enabling simpler, more adaptive ways for people to interact with financial services.
- Currently developing MVP and navigating licensing requirements.
- Multidisciplinary team of 100+ people representing 20+ nationalities.
- Headquarters in the UAE and offices in Portugal and Ukraine.
- United behind a shared ambition and a relentless focus on serving customers.